Focal Cerebral Arteriopathy of Childhood
Bibliographic record
Abstract
Background and Purpose- Focal cerebral arteriopathy (FCA)-a common cause of arterial ischemic stroke in previously healthy children-often progresses over days to weeks, increasing the risk of recurrent stroke. We developed a novel severity scoring system designed to quantify FCA progression and correlate with clinical outcomes. Methods- The VIPS study (Vascular Effects of Infection in Pediatric Stroke) prospectively enrolled 355 children with arterial ischemic stroke (2010-2014), including 41 with centrally confirmed FCA. Two neuroradiologists independently reviewed FCA cerebrovascular imaging, assigning a graded severity score of zero (no involvement) to 4 (occlusion) to individual arterial segments. The FCA severity score (FCASS) was the unweighted sum. In an iterative process, we modeled scores derived from different combinations of arterial segments to identify the model that optimized correlation with clinical outcome, simplicity, and reliability. Results- The optimal FCASS summed scores from 5 arterial segments: supraclinoid internal carotid artery, A1, A2, M1, and M2. The median (interquartile range) baseline FCASS was 4 (2-6). Of 33 children with follow-up imaging, the maximum FCASS (at any time point) was 7 (5-9). Twenty-four (73%) had FCA progression on follow-up with their maximum FCASS at a median of 8 (5-35.5) days poststroke; their median FCASS increase was 4 (2.5-6). FCASS did not correlate with recurrent arterial ischemic stroke. Maximum (but not baseline) FCASS correlated with 1-year pediatric stroke outcome measures ( P=0.037). Conclusions- Our novel scoring system for FCA severity correlates with neurological outcomes in the VIPS cohort and provides a tool for FCA treatment trials under development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".